print.Ckmeans.1d.dp: Print Optimal Univariate Clustering Results

In Ckmeans.1d.dp: Optimal, Fast, and Reproducible Univariate Clustering

Print Optimal Univariate Clustering Results

Description

Print optimal univariate clustering results obtained from Ckmeans.1d.dp or Ckmedian.1d.dp.

Usage

## S3 method for class 'Ckmeans.1d.dp'
print(x, ...)
## S3 method for class 'Ckmedian.1d.dp'
print(x, ...)

Arguments

x	object returned by calling Ckmeans.1d.dp or Cksegs.1d.dp.
...	arguments passed to print function.

Details

Function print.Ckmeans.1d.dp and print.Ckmedian.1d.dp prints the maximum ratio of between-cluster sum of squares to total sum of squares unless all input elements are zero. The ratio is an indicator of maximum achievable clustering quality given the number of clusters: 100% for a perfect clustering and 0% for no cluster patterns.

Value

An object of class "Ckmeans.1d.dp" or "Ckmedian.1d.dp" as defined in Ckmeans.1d.dp.

Author(s)

Joe Song and Haizhou Wang

Examples

# Example: clustering data generated from a Gaussian
#          mixture model of two components
x <- c(rnorm(15, mean=-1, sd=0.3),
       rnorm(15, mean=1, sd=0.3))
res <- Ckmeans.1d.dp(x)
print(res)

res <- Ckmedian.1d.dp(x)
print(res)

y <- (rnorm(length(x)))^2
res <- Ckmeans.1d.dp(x, y=y)
print(res)

res <- Ckmedian.1d.dp(x)
print(res)

Ckmeans.1d.dp documentation built on Aug. 20, 2023, 1:08 a.m.